A Comparative Analysis of CNN Models in Deep Learning for Leaf Disease Detection

Author(s)	Jayamma Rodda, R. Hema Chandrika, Ch.Devi Durga
Country	India
Abstract	order to detect the disease in plant a Convolutional Neural Network(CNN) with the help of image processing beside is in use here in our paper. A Convolutional Neural Network is an artificial neural network which is specially designed to deal with image recognition[1] tasks when an image is input. Here the idea is to use CNN models to spot diseases in apple, grape, corn and potato. This idea is to use CNN models to spot diseases in apple, grape, corn, and potato plants. We proposed an algorithm. This paper mainly focused on CNN models CNN, AlexNet,VGG16 in deep learning that will be compared in the study
Keywords	Image classification, Deep Learning, leaf disease, Convolutional Neural Network, Alex Net, VGG16.
Field	Computer > Data / Information
Published In	Volume 5, Issue 5, September-October 2023
Published On	2023-09-03
Cite This	A Comparative Analysis of CNN Models in Deep Learning for Leaf Disease Detection - Jayamma Rodda, R. Hema Chandrika, Ch.Devi Durga - IJFMR Volume 5, Issue 5, September-October 2023. DOI 10.36948/ijfmr.2023.v05i05.6041
DOI	https://doi.org/10.36948/ijfmr.2023.v05i05.6041
Short DOI	https://doi.org/gsn75g

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